Using Modified Bagging and Boosting Algorithms in Multiple Classifiers System for Remote Sensing Image Classification

多分類器系統中Bagging and Boosting法則的改進

曾裕強(Y. C. Tzeng) ； 陳錕山(Kun-Shan Chen) ； 周念湘(N. S. Chou)

《航測及遙測學刊》 12卷3期 (2007/09) Pp. 241-256

https://doi.org/10.6574/JPRS.2007.12(3).4

摘要

本文針對多分類器系統中提出一修正後的Bagging and Boosting票決方式來改善遙測影像中地物分類的精度，並藉由引進一信心指標，多分類器系統可以增加各分類器成間的差異度或降低模糊度。我們利用雷達影像與光學影像的融合來測試多分類器系統的分類性能。實驗結果顯示新的多分類器系統可大幅提升整體的分類精度。

關鍵字

多分類器系統 ； 遙測影像

並列摘要

In this paper, modified Bagging and Boosting voting methods were proposed in the multiple classifiers system for terrain classification of remote sensing images. The improvement is achieved by introducing a confidence index to reduce the ambiguities among the targets being classified. Performance of the proposed multiple classifiers system was tested using fused radar and optical images. Experimental results show that the classifier is able to substantially improve the classification accuracy.

並列關鍵字

multiple classifiers system ； Bagging and Boosting ； remote sensing image